58 A hospital paediatrics education curriculum: Quality improvement for inpatient paediatric learner education on CTU
Notice bibliographique
Résumé
Abstract Background Paediatric learners experience the bulk of their inpatient medicine on the wards. While bedside teaching is invaluable, ward learning can be impacted by seasonal exposure, clinical homogeneity, and volume. Locally our learners requested more formal ward teaching to encourage dialogue around common topics perhaps not encountered on rotation. We queried whether having a database of interactive guideline-based educational experiences would minimize barriers (eg. time, resources) to providing formal inpatient learner education. Objectives We sought to enhance general paediatrics ward teaching by developing a curriculum of guideline-based interactive educational content on common inpatient paediatric topics. Design/Methods This study was conducted at a Canadian tertiary care paediatric hospital with a range of learners (MSI3, MSI4, paediatric residents (R1-R4)) over 12 months. 1) Needs Assessment: We surveyed residents, hospitalist fellows, and CTU physicians regarding a) perceived need for a curriculum, b) content (top 5 CPS guidelines and top 5 non-CPS topics), c) teaching modality, d) need for handouts, and e) curriculum structure. 2) Curriculum generation: Curriculum was developed according to needs assessment results. 3) Quality improvement: Learners were surveyed after each session with four Likert scale questions (5=strongly agree) regarding teaching quality, clinical translatability, enhanced knowledge/understanding, and improved clinical confidence. Results 1) Needs assessment: Needs assessment (N=25) unanimously supported a structured curriculum. Eleven CPS statements and twelve non-CPS guideline-based topics were identified for content. Three preferred teaching formats were highlighted, and handouts were important to 88% of respondents. The curriculum was favoured to be 50-75% standardized. 2) Curriculum generation: We developed a curriculum of 13 topics with different delivery modalities (e.g. case-based powerpoints, whiteboard talks, Jeopardy, simulation). All were guideline-based, interactive, and had fill-in-the-blank learner handouts. The curriculum was standardized with 4/6 CTU teaching sessions per block being derived from the curriculum bank, and the remainder being at educator discretion (e.g. curriculum bank, interesting case). 3) Quality improvement: Likert scales (5=strongly agree) were positive from all learners (MSI3-R4; N=52), with scores of 4.9+/-0.2 for teaching quality, translatability to practice, and improved understanding, and 4.8+/-0.3 for improved clinical confidence. Conclusion Here we present an interactive and guideline-based paediatric inpatient learner education curriculum whose development, from content to delivery modality, was directed by community needs. We are now seeking funding to prepare for national distribution (e.g. peer-review, licensure), and intend to publish on platform where the curriculum would be downloadable for use by all educators (i.e. senior residents, staff).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».